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040 _aBTCTA
_beng
_cBTCTA
_erda
_dYDXCP
_dBDX
_dOCLCQ
_dJBL
_dAPL
_dTEF
082 0 4 _a005.133
_223
_bMUI
100 1 _aM�uller, Andreas C.,
_eauthor.
_963362
245 1 0 _aIntroduction to machine learning with Python :
_ba guide for data scientists /
_cAndreas C. M�uller and Sarah Guido.
246 3 0 _aMachine learning with Python
250 _aFirst edition.
264 1 _aSebastopol, CA :
_bO'Reilly Media, Inc.,
_c2016.
264 4 _c�2017
300 _axii, 378 pages :
_billustrations ;
_c24 cm
338 _avolume
_bnc
_2rdacarrier
500 _aIncludes index.
505 0 _aIntroduction -- Supervised learning -- Unsupervised learning and preprocessing -- Representing data and engineering features -- Model evaluation and improvement -- Algorithm chains and pipelines -- Working with text data -- Wrapping up.
520 _aMachine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas M�uller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. --
_cProvided by publisher.
650 0 _aPython (Computer program language)
_937691
650 0 _aProgramming languages (Electronic computers)
_937692
650 0 _aData mining.
_937693
650 7 _aData mining.
_2fast
_0(OCoLC)fst00887946
_937693
650 7 _aProgramming languages (Electronic computers)
_2fast
_0(OCoLC)fst01078704
_937692
650 7 _aPython (Computer program language)
_2fast
_0(OCoLC)fst01084736
_937691
650 7 _aMaschinelles Lernen
_2gnd
_963363
700 1 _aGuido, Sarah,
_eauthor.
_963364
942 _2ddc
_cBK
999 _c84953
_d84953